CN115036993B - Energy device control method, device, electronic apparatus, and computer-readable medium - Google Patents
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- G06Q50/06—Electricity, gas or water supply
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
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Abstract
Embodiments of the present disclosure disclose energy device control methods, devices, electronic devices, and computer readable media. One embodiment of the method comprises: acquiring an energy device information set corresponding to a virtual power plant; generating energy acquisition value information corresponding to the energy device information for each energy device information included in the energy device information set according to the energy device name, the energy device parameter information, and the energy device number included in the energy device information; acquiring value information based on a preset constraint condition set and each generated energy, and generating an energy scheduling target value and parameter information of each target energy device; and controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device. The implementation mode can improve the comprehensiveness of the energy scheduling parameters, thereby improving the applicability of the scheduling scheme and further improving the effect of controlling the energy source device to realize energy conservation and emission reduction during the operation of the virtual power plant.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a method and an apparatus for controlling an energy device, an electronic device, and a computer-readable medium.
Background
Under the target background of 'carbon peak reaching and carbon neutralization', the coupling of different energy forms such as electricity, gas, heat, hydrogen and the like is increasingly close, and the randomness and uncertainty of the output of renewable energy in the virtual power plant bring challenges for controlling an energy device to realize the energy scheduling of the virtual power plant. At present, when the energy scheduling of a virtual power plant is realized by controlling an energy device, the commonly adopted method is as follows: and controlling a single energy device to realize energy scheduling of the virtual power plant by a random optimization method.
However, when the energy device is controlled to implement the energy scheduling of the virtual power plant in the above manner, the following technical problems often exist:
firstly, a single energy device is controlled to realize energy scheduling of a virtual power plant through a random optimization method, the comprehensiveness of parameter information which influences the energy scheduling is considered to be poor, and the applicability of the determined scheduling scheme is poor, so that the effect of controlling the energy device to realize energy conservation and emission reduction during the operation of the virtual power plant is poor.
Secondly, the probability distribution obtained by the random optimization method is low in accuracy, and the scheduling scheme determined by the method is poor in applicability, so that the effect of controlling the energy device to achieve energy conservation and emission reduction during operation of the virtual power plant is poor.
The above information disclosed in this background section is only for enhancement of understanding of the background of the inventive concept and, therefore, it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art in this country.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose a method, an apparatus, an electronic device, a computer readable medium of energy apparatus control to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a method of energy device control, the method comprising: acquiring an energy device information set corresponding to each energy device of a virtual power plant, wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information and an energy device number; generating energy acquisition value information corresponding to the energy device information for each energy device information included in the energy device information set, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information; generating an energy scheduling target value and parameter information of each target energy device based on a preset constraint condition set and the generated value information of each energy acquisition, wherein the constraint condition set comprises constraint conditions representing constraint on at least one piece of energy device parameter information included in the energy device information set; and controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device.
In a second aspect, some embodiments of the present disclosure provide an energy device control device, the device comprising: an acquisition unit configured to acquire an energy device information set corresponding to each energy device of a virtual power plant, wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information, and an energy device number; a first generation unit configured to generate energy acquisition value information corresponding to the energy device information, for each energy device information included in the energy device information set, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information; a second generating unit configured to generate an energy scheduling target value and each target energy device parameter information based on a preset constraint condition set and each generated energy acquisition value information, wherein the constraint condition set includes a constraint condition representing that at least one energy device parameter information included in the energy device information set is constrained; and the control unit is configured to control each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.
The above embodiments of the present disclosure have the following advantages: by the energy device control method of some embodiments of the disclosure, comprehensiveness of energy scheduling parameters can be improved, so that applicability of a scheduling scheme is improved, and effects of energy conservation and emission reduction during operation of a virtual power plant are further improved by controlling the energy device. Specifically, cause the relatively poor reason of energy saving and emission reduction when control energy device realizes the operation of virtual power plant to lie in: the energy dispatching of the virtual power plant is realized by controlling a single energy device through a random optimization method, the comprehensiveness of the parameter information which influences the energy dispatching is considered to be poor, and the applicability of the determined dispatching scheme is poor, so that the effect of controlling the energy device to realize energy conservation and emission reduction during the operation of the virtual power plant is poor. Based on this, the energy device control method of some embodiments of the present disclosure first obtains an energy device information set corresponding to each energy device of the virtual power plant. Wherein each of the energy device information included in the energy device information set includes an energy device name, energy device parameter information, and an energy device number. Therefore, parameter information which affects energy scheduling comprehensively can be obtained, and the parameter information can be used for generating value information of each energy source. Next, for each energy device information included in the energy device information set, energy acquisition value information corresponding to the energy device information is generated based on the energy device name, the energy device parameter information, and the energy device number included in the energy device information. Thus, the obtained energy acquisition value information can be used as value constraint for generating the energy scheduling target value and the parameter information of each target energy device. Then, based on the preset constraint condition set and the generated value information of each energy acquisition, an energy scheduling target value and parameter information of each target energy device are generated. Wherein the set of constraints includes constraints characterizing constraints that constrain at least one energy device parameter information included in the set of energy device information. Therefore, the optimized energy scheduling target value and the parameter information of each target energy device can be obtained, and a scheduling scheme with good adaptability is determined according to the obtained optimized energy scheduling target value and the parameter information of each target energy device. And finally, controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device. Therefore, each energy device of the virtual power plant can be controlled to execute the energy scheduling task according to the scheduling scheme. And the parameter information influencing energy scheduling is considered relatively comprehensively, and the scheduling scheme is determined according to the parameter information, so that the applicability of determining the scheduling scheme according to the parameter information can be improved. And each energy device of the virtual power plant can be controlled to execute an energy scheduling task according to the scheduling scheme, so that the effect of controlling the energy devices to realize energy conservation and emission reduction during the operation of the virtual power plant is improved. Therefore, the comprehensiveness of the energy dispatching parameters can be improved, the applicability of the dispatching scheme is improved, and the effect of energy conservation and emission reduction during the operation of the virtual power plant is further improved by controlling the energy source device.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and components are not necessarily drawn to scale.
Fig. 1 is a flow diagram of some embodiments of an energy device control method according to the present disclosure;
fig. 2 is a schematic structural diagram of some embodiments of an energy device control device according to the present disclosure;
FIG. 3 is a schematic block diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and the embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence of the functions performed by the devices, modules or units.
It is noted that references to "a" or "an" in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will appreciate that references to "one or more" are intended to be exemplary and not limiting unless the context clearly indicates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates a flow 100 of some embodiments of an energy device control method according to the present disclosure. The energy device control method comprises the following steps:
In some embodiments, an execution subject (e.g., a computer device) of the energy device control method may acquire the energy device information sets of the respective energy devices corresponding to the virtual power plant through a wired connection manner or a wireless connection manner. The virtual power plant may be a power supply coordination management system that realizes aggregation and coordination optimization of Distributed Energy Resources (DER) such as Distributed Generators (DG), energy storage systems, controllable loads, electric vehicles, and the like through an advanced information communication technology and a software system, so as to participate in power market and power grid operation as a special power plant. Each of the energy device information included in the energy device information set may include an energy device name, energy device parameter information, and an energy device number. The energy devices included in the respective energy devices correspond one-to-one to the energy device information included in the energy device information set. Each energy device can comprise a photovoltaic system, a cogeneration unit, an electric-to-gas device, an energy storage device and an electric automobile. The number of the photovoltaic systems included in each energy device, the number of the included cogeneration units, the number of the included electric-to-gas conversion devices, the number of the included energy storage devices, and the number of the included electric vehicles are not limited. The energy device corresponding to the photovoltaic system may be referred to as a "photovoltaic system". The energy device parameter information corresponding to the photovoltaic system may include unit operation value information (for example, unit operation cost) and unit light abandon value information (for example, unit light abandon cost) of the photovoltaic system, each light abandon power at each scheduling time, each actual output power, and each predicted output power. The unit operation value information can be the unit value required to be paid for operating the photovoltaic system. The unit of the unit value may be "yuan/kw". The unit abandoning value information may be preset value information required for abandoning unit optical energy power generation. The predicted output power may be a power preset according to weather conditions. The scheduling time may be a time when energy scheduling is performed. The abandoned light power can be the power of the power generated by the photovoltaic system abandoned. The number of the energy devices corresponding to the photovoltaic system may be the number of the photovoltaic systems included in each of the energy devices. The energy device corresponding to the cogeneration unit may be referred to as a "cogeneration unit". The above-described cogeneration unit may be a cogeneration unit including a carbon capture facility. The energy device parameter information corresponding to the cogeneration unit may be startup value information (for example, startup cost), shutdown value information (for example, shutdown cost), unit operation value information (for example, unit operation cost), a ramp rate, a maximum value and a minimum value of natural gas consumption rate, carbon emission intensity, carbon emission amount, electric-to-heat conversion coefficient, natural gas-to-electric conversion coefficient and natural gas-to-heat conversion coefficient, respective natural gas consumption rates at respective scheduling times, respective startup state variables, respective shutdown state variables, respective startup flag variables, respective shutdown flag variables, respective output thermal powers, respective output electric powers, and carbon capture device parameter information of the cogeneration unit. The carbon capture plant parameter information may be parameter information when the carbon capture plant is operating. The above-described carbon capture plant parameter information may include consumed electric power capturing a unit amount of carbon dioxide, maintenance energy consumption, operation energy consumption, carbon turnover value information (e.g., carbon trading cost), carbon capture efficiency, carbon capture value information (e.g., carbon capture cost), maintenance energy consumptions at scheduling timings, operation energy consumptions, carbon capture energy consumptions, and captured carbon dioxide amounts. The amount of carbon dioxide may be the mass of carbon dioxide. The number of the energy devices corresponding to the cogeneration unit may be the number of the energy devices including the cogeneration unit. The startup value information may be value information for starting the cogeneration unit. The shutdown value information may be value information for shutting down the cogeneration unit. The natural gas consumption rate may be a consumption rate of natural gas. The maximum value and the minimum value of the natural gas consumption rate may be set in advance. The electric-to-heat conversion coefficient may be a preset conversion coefficient for converting electric energy of the cogeneration unit into heat energy. The conversion coefficient of natural gas to electricity may be a preset conversion coefficient of natural gas to electric energy of the cogeneration unit. The natural gas to heat conversion coefficient may be a preset conversion coefficient for converting natural gas of the cogeneration unit into heat energy. The startup state variable may be a variable that represents whether the cogeneration unit is adjusted from a shutdown state to a startup state. For example, 0 may indicate that the cogeneration unit has not been adjusted from a shutdown state to a startup state. 1 may represent a variable for adjusting the cogeneration unit from a shutdown state to a startup state. The boot state variable may be 0 or 1. The shutdown state variable may be a variable of whether the cogeneration unit is adjusted from a startup state to a shutdown state. The shutdown state variable may be 0 or 1. The startup flag variable may be a variable indicating whether the cogeneration unit is started up. The start flag variable may be 0 or 1. The shutdown flag variable may be a variable indicating whether the cogeneration unit is shutdown. The stop flag variable may be 0 or 1. The output thermal power may be output thermal power. The above-mentioned output electric power may be an output electric power. The name of the energy device corresponding to the electric gas conversion equipment can be 'electric gas conversion equipment'. The electric gas conversion device can comprise an electric hydrogen production device and a hydrogen methanation device. The energy device parameter information corresponding to the electric gas conversion equipment may include unit operation value information (for example, unit operation cost) of the electric gas conversion equipment, each electric power consumed at each scheduling time, electric hydrogen production equipment parameter information, and hydrogen methanation equipment parameter information. The parameter information of the electrical hydrogen production equipment can be parameter information of the electrical hydrogen production equipment during operation. The electrical hydrogen plant parameter information may include a ramp rate, a conversion rate, a maximum consumed electrical power, individual hydrogen production rates at individual scheduled times, individual electrical powers consumed. The parameter information of the hydrogen methanation equipment can be parameter information of the hydrogen methanation equipment during operation. The above-mentioned hydrogen methanation apparatus parameter information may include a ramp rate, a ratio of a reaction amount of hydrogen to a reaction amount of carbon dioxide in methanation reaction, a maximum hydrogen production rate, respective natural gas production rates at respective scheduling timings, respective hydrogen consumption rates, and respective carbon dioxide consumption rates. The above-described maximum consumed electric power may be a maximum value of consumed electric power set in advance. The maximum hydrogen production rate may be a preset maximum hydrogen production rate. The number of the energy devices corresponding to the electric gas conversion device may be the number of the electric gas conversion devices included in each energy device. The energy device name corresponding to the energy storage device may be "energy storage device". The energy storage device may include an electrical energy storage device, a thermal energy storage device, a natural gas energy storage device, a hydrogen storage device. The energy device parameter information corresponding to the energy storage device may include electrical energy storage device parameter information, thermal energy storage device parameter information, natural gas energy storage device parameter information, and hydrogen storage device parameter information. The parameter information of the electrical energy storage device may be parameter information of the electrical energy storage device during operation. The parameter information of the thermal energy storage device may be parameter information of the thermal energy storage device during operation. The parameter information of the natural gas energy storage device can be parameter information of the natural gas energy storage device during operation. The hydrogen storage device parameter information may be parameter information of the hydrogen storage device during operation. The electrical energy storage device parameter information, the thermal energy storage device parameter information, the natural gas energy storage device parameter information, and the hydrogen storage device parameter information may each include unit operation value information (e.g., unit operation cost), a maximum value of input power, a minimum value of input power, a maximum value of output power, a minimum value of output power, an energy dissipation rate, a charging efficiency, a discharging efficiency, initial stored energy, a maximum value and a minimum value of stored energy, each input power at each scheduling time, each output power, and each stored energy. The maximum value of the input power, the minimum value of the input power, the maximum value of the output power, and the minimum value of the output power may be set in advance. The energy dissipation ratio may be a loss amount per unit time of the energy storage device in a non-charging and non-discharging state. The unit time may be one hour. The initial stored energy, the maximum value and the minimum value of the stored energy may be set in advance. The number of the energy devices corresponding to the energy storage device may be the sum of the numbers of the electrical energy storage device, the thermal energy storage device, the natural gas energy storage device and the hydrogen storage device included in the energy storage device. The energy device corresponding to the electric vehicle may be named as "electric vehicle". The energy device parameter information corresponding to the electric vehicle may include a hundred kilometers of power consumption, a rated capacity, a total mileage of travel, a mean value and a variance of mileage of daily travel, a charging efficiency, a discharging efficiency, a provided battery capacity, a state of charge at each time, and a state of charge at a zero time of the electric vehicle. The power consumption per hundred kilometers may be power consumed for one hundred kilometers of travel. The average and variance of the daily driving mileage may be the average and variance of each daily driving mileage included in the driving history data of the electric vehicle. The total mileage may be a sum of mileage traveled per day included in the travel history data of the electric vehicle. The number of the energy devices corresponding to the electric vehicle may be the number of the electric vehicles included in each of the energy devices. It is noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a UWB (ultra wideband) connection, and other wireless connection means now known or developed in the future.
In some embodiments, for each energy device information included in the energy device information set, the execution subject may generate energy acquisition value information corresponding to the energy device information according to an energy device name, energy device parameter information, and an energy device number included in the energy device information. The energy acquisition value information may be value information of energy acquisition (for example, the energy acquisition value information may be energy acquisition cost). In practice, the execution subject may generate the energy acquisition value information corresponding to the energy device information by:
in a first step, in response to determining that the energy device corresponding to the energy device information is the photovoltaic system, energy acquisition value information corresponding to the photovoltaic system may be generated according to the following formula:
wherein, in the formula (1)，
The total light rejection value information (e.g., total light rejection cost) of the photovoltaic system can be represented. The total light abandoning value information can be the total value information of the abandoning light.
And the unit abandon price information of the photovoltaic system can be represented.
Can represent a photovoltaic system
At the scheduling time
The optical power of the waste light.
A set of scheduling instants may be represented. The scheduling time set may include scheduling times in a cycle of a scheduling period in a day.
It is possible to represent the individual photovoltaic systems comprised by the individual energy devices described above.
One scheduling period may be represented. The scheduling period may be 15 minutes or 1 hour. In the formula (2), the reaction mixture is,
the total value information of the equipment operation (for example, the total cost of the equipment operation) of the photovoltaic system can be represented.
Can represent a photovoltaic system
The unit running value information of (a).
Can represent a photovoltaic system
At the scheduling time
The actual output power.
In response to determining that the energy device corresponding to the energy device information is the cogeneration unit, generating energy acquisition value information corresponding to the cogeneration unit according to the following formula:
wherein, in the formula (3),
the total start-stop value information (e.g., total start-stop cost) of the cogeneration unit may be represented.
It can be said that each of the above-mentioned energy means comprises a cogeneration unit.
Can represent a cogeneration unit
The boot value information.
Can represent a cogeneration unit
At the scheduled time
The boot state variable of (1).
Can represent a cogeneration unit
The shutdown value information.
Can represent a cogeneration unit
At the scheduling time
The shutdown state variable of (1). In the formula (4), the reaction mixture is,
the plant operation total value information (e.g., the plant operation total cost) of the above-described cogeneration unit may be represented.
Can represent a cogeneration unit
The unit running value information of (c).
Can represent a cogeneration unit
At the scheduled time
Natural gas consumption rate of (c). In the formula (5), the reaction mixture is,
value information (e.g., carbon trading costs) that may represent the carbon turnover of a carbon capture plant included in a cogeneration unit.
Carbon streaming value information may be represented.
Can represent a cogeneration unit
At the scheduled time
To output electric power.
Can represent a cogeneration unit
At the scheduled time
The output thermal power.
Can represent the carbon emission intensity of the cogeneration unit.
May represent the carbon credit of the cogeneration unit.
It is possible to express the carbon capture efficiency of the carbon capture plant included in the cogeneration unit. In the formula (6), the reaction mixture is,
may represent value information of carbon storage (e.g., cost of carbon storage) of a carbon capture plant included in the cogeneration unit.
The unit carbon capture value information of each of the above carbon capture devices can be represented.
Can represent a carbon capture facility
At the scheduling time
The carbon capture efficiency of (2).
It is possible to represent each of the carbon capture devices included in each of the cogeneration units described above. In the formula (7), the reaction mixture is,
value information (e.g., carbon trading costs and carbon storage costs) of carbon flows and storage of carbon capture equipment included in a cogeneration unit can be represented.
Third, in response to determining that the energy device corresponding to the energy device information is the electrical conversion equipment, energy acquisition value information corresponding to the electrical conversion equipment may be generated according to the following equation:
wherein, in the formula (8),
may represent total equipment operational value information (e.g., total equipment operational cost) for the electrical conversion equipment described above.
May represent the electrical conversion equipment comprised by each of the energy devices described above.
Can represent an electric gas conversion device
The unit running value information of (a).
Can represent an electric gas conversion device
At the scheduled time
The consumed electric power.
Fourth, in response to determining that the energy device corresponding to the energy device information is the energy storage device, energy acquisition value information corresponding to the energy storage device may be generated according to the following equation:
wherein, in the formula (9),
may represent the total device operational value information (e.g., total device operational cost) for the energy storage device.
Can represent the energy storage type set included by the energy storage device. The set of energy storage types may include electrical energy storage, thermal energy storage, natural gas energy storage, and hydrogen storage.
It can be shown that the energy storage type set comprises energy storage types of
The set of energy storage devices.
May represent an energy storage device as
Of the energy storage device
The unit running value information of (a).
Can indicate the type of energy storage as
Energy storage device of
At the scheduling time
The input power of (1).
Can indicate the type of energy storage as
Of the energy storage device
At the scheduled time
The output power of (1).
And fifthly, generating total operation value information of the energy device equipment according to the equipment operation value information corresponding to each energy device and the following formula:
wherein, in the formula (10),
the energy device equipment operational total value information (e.g., energy device equipment operational total cost) may be represented.
And 103, generating an energy scheduling target value and parameter information of each target energy device based on the preset constraint condition set and the generated value information of each energy acquisition device.
In some embodiments, the execution subject may generate the energy scheduling target value and the parameter information of each target energy device based on a preset constraint condition set and the generated value information of each energy acquisition device. Wherein the set of constraints may represent constraints that constrain at least one energy device parameter information included in the set of energy device information. The energy scheduling target value may be a minimum value of the energy scheduling operation total value information (e.g., energy scheduling operation cost). The target energy device parameter information may include target energy device parameter information corresponding to a photovoltaic system, target energy device parameter information corresponding to a cogeneration unit, target energy device parameter information corresponding to a power-to-gas conversion device, target energy device parameter information corresponding to an electric energy storage device, target energy device parameter information corresponding to a thermal energy storage device, target energy device parameter information corresponding to a natural gas energy storage device, target energy device parameter information corresponding to a hydrogen storage device, target energy device parameter information corresponding to an electric vehicle, target energy device parameter information corresponding to an energy network, and target energy device parameter information corresponding to a load. The parameter information of each target energy device corresponding to the photovoltaic system may include each abandoned light power and each output power of each photovoltaic system at each scheduling time. The parameter information of each target energy device corresponding to the cogeneration unit may include each natural gas consumption rate, each start-up state variable, each stop state variable, each start-up flag variable, each stop flag variable, each output thermal power, each output electric power, and the parameter information of the target energy device of the carbon capture device at each scheduling time of each cogeneration unit. The parameter information of the target energy device of the carbon capture facility may be parameter information of the carbon capture facility when the carbon capture facility operates at a scheduled time. The above-mentioned carbon capture equipment target energy device parameter information may include each maintenance energy consumption, each operation energy consumption, each carbon capture energy consumption, and each amount of captured carbon dioxide of each carbon capture equipment at each scheduling time. The above-mentioned respective target energy device parameter information of the corresponding electric conversion equipment may include respective electric power consumed by each electric conversion equipment at respective scheduling timings, electric hydrogen production equipment target energy device parameter information, and hydrogen methanation equipment target energy device parameter information. The parameter information of the target energy device of the electrical hydrogen production equipment can be parameter information of the electrical hydrogen production equipment when the electrical hydrogen production equipment operates at a scheduling time. The target energy device parameter information of the electrical hydrogen production facility may include individual hydrogen production rates and individual consumed electrical powers of each electrical hydrogen production facility at individual scheduling times. The parameter information of the target energy device of the hydrogen methanation equipment can be parameter information of the hydrogen methanation equipment when the hydrogen methanation equipment operates at a scheduling moment. The above hydrogen methanation apparatus target energy device parameter information may include respective natural gas production rates, respective hydrogen consumption rates, and respective carbon dioxide consumption rates of each hydrogen methanation apparatus at respective scheduling timings. The parameter information of each target energy device corresponding to the electrical energy storage device may be parameter information of the electrical energy storage device when the electrical energy storage device operates at the scheduling time. The parameter information of each target energy device corresponding to the thermal energy storage device may be parameter information of the thermal energy storage device when the thermal energy storage device operates at a scheduling time. The parameter information of each target energy device corresponding to the natural gas energy storage device may be parameter information of the natural gas energy storage device when the natural gas energy storage device operates at a scheduling time. The parameter information of each target energy device corresponding to the hydrogen storage equipment may be parameter information of the hydrogen storage equipment when the hydrogen storage equipment operates at a scheduling time. The parameter information of each target energy device corresponding to the electrical energy storage apparatus, the parameter information of each target energy device corresponding to the thermal energy storage apparatus, the parameter information of each target energy device corresponding to the natural gas energy storage apparatus, and the parameter information of each target energy device corresponding to the hydrogen storage apparatus may include each input power, each output power, and each stored energy at each scheduling time. The parameter information of each target energy device of the electric vehicle may include a state of charge of each electric vehicle at each scheduling time, a state of charge of each electric vehicle at a zero time, and a provided battery capacity. The parameter information of each target energy device corresponding to the energy grid may include electric quantity, heat quantity, and natural gas quantity acquired from the energy grid. The target energy device parameter information for each load may include a load type for each load that can be transferred and interrupted at each scheduling time. The energy network may be a network providing various energies. The set of load types may include electrical, thermal, and hydrogen loads. The constraint condition set can comprise constraint conditions of all photovoltaic systems, constraint conditions of all electric-to-gas equipment, constraint conditions of all cogeneration units, constraint conditions of all energy storage equipment, constraint conditions of all electric vehicles, response constraint conditions of all comprehensive demand sides, all standby constraint conditions and all energy balance constraint conditions. The above-mentioned individual photovoltaic system constraints may be expressed according to the following formula:
wherein, in the formula (11),
can represent a photovoltaic system
At the scheduled time
The output power of (1).
Can represent a photovoltaic system
At the scheduling time
The predicted output power of (2).
The above-mentioned constraint condition of each electric power conversion equipment can be expressed according to the following formula:
wherein, in the formula (13),
can represent an electric gas conversion device
Comprising an electrical hydrogen production plant at scheduled times
Hydrogen production rate.
May represent the conversion of an electrical hydrogen plant comprising the electrical gas conversion plant. The formula (13) can represent an electric gas conversion device
The relationship between hydrogen production rate and electrical power consumed by the included electrical hydrogen production apparatus. In the formula (14), the compound represented by the formula (I),
can represent an electric gas conversion device
Comprising an electrical hydrogen production plant at scheduled times
The electrical power consumed.
Can represent an electric gas conversion device
Including a minimum ramp rate of the electrohydrogen plant.
Can represent an electric gas conversion device
Including the maximum value of the ramp rate of the electrohydrogen plant. In the formula (15), the reaction mixture is,
can represent an electric gas conversion device
Comprising an electrical hydrogen production plant at scheduled times
Maximum value of consumed electric power. The expressions (14) and (15) may represent an electric gas-converting apparatus
Including ramp rate limits for the electro-hydrogen plant and electrical power limits for consumption. In the formula (16), the compound represented by the formula (I),
can represent an electric gas conversion device
Comprising a hydrogen methanation device at the scheduled time
Natural gas production rate.
Can represent an electric gas conversion device
The included hydrogen methanation equipment is at the scheduling moment
Hydrogen consumption rate of (2).
May represent the conversion of a hydrogen methanation facility comprised by the electrical conversion facility. Equation (16) may represent an electric gas-converting apparatus
The relationship between natural gas production rate and hydrogen consumption rate of the included hydrogen methanation apparatus. In the formula (17), the reaction mixture is,
can represent an electric gas conversion device
The included hydrogen methanation equipment is at the scheduling moment
The carbon dioxide consumption rate of (2).
Can represent the reaction amount of hydrogen in the methanation reaction of the hydrogen methanation equipmentAnd the reaction amount of carbon dioxide. The formula (17) can represent an electric gas conversion device
Including the relationship between carbon dioxide consumption and hydrogen consumption in a hydrogen methanation plant. In the formula (18), the reaction mixture is,
can represent an electric gas conversion device
Including a maximum value for the natural gas production rate of the hydrogen methanation apparatus. In the formula (19), the compound represented by the formula (I),
can represent an electric gas conversion device
Including a minimum value of the ramp rate of the hydrogen methanation apparatus.
Can represent an electric gas conversion device
Including a maximum value for the ramp rate of the hydrogen methanation apparatus. The expressions (18) and (19) may represent an electric gas-converting apparatus
Including natural gas productivity limitations and ramp rate limitations of the hydrogen methanation apparatus.
The above-described constraint conditions of each cogeneration unit can be expressed according to the following formula:
wherein, in the formula (20),
the electric-to-heat conversion coefficient of the cogeneration unit can be expressed. The formula (20) may represent a cogeneration unit
Electrical output power and thermal output power. In the formula (21), the compound represented by the formula,
can represent the natural gas to electricity conversion coefficient of the cogeneration unit.
Can represent the natural gas to heat conversion coefficient of the cogeneration unit. The formula (21) can represent a cogeneration unit
The consumption of natural gas in relation to electrical power and thermal power. In the formula (22), the reaction mixture is,
can represent a cogeneration unit
Is the minimum value of the ramp rate of (c).
Can represent a cogeneration unit
Is measured. In the formula (23), the reaction mixture is,
can represent a cogeneration unit
Of the natural gas consumption rate of (c).
Can represent a cogeneration unit
Maximum natural gas consumption rate.
Can represent a cogeneration unit
At the scheduled time
The unit start flag variable. The formulae (22) and (23) may represent a cogeneration unit
And a limitation of the ramp rate of the gas turbine and a limitation of the consumption of natural gas thereof. Formula (24) can restrain cogeneration unit
The power-on status, the power-off status, and the relationship between the power-on flag and the power-off flag. Formula (25) can limit cogeneration units
Cannot be turned on and off simultaneously. In the formula (26), the reaction mixture is,
can represent a cogeneration unit
Number of power-on to power-off times. Equation (26) may limit the maximum number of starts and stops within the scheduled time. In the formula (27), the reaction mixture is,
can represent a carbon capture apparatus
At the scheduled time
Energy consumption for carbon capture.
Can represent a carbon capture apparatus
At the scheduled time
The maintenance energy consumption of.
May be a preset value.
Can represent a carbon capture apparatus
At the scheduling time
The operation energy consumption of (2). In the formula (28), the reaction mixture is,
may represent the electrical power consumption of each of the above carbon capture units to capture carbon dioxide. The above-mentioned electric power consumption may be consumed electric power.
Can represent a carbon capture facility
At the scheduling time
The amount of carbon dioxide captured.
The various energy storage device constraints described above may be expressed according to the following equation:
wherein, in the formula (30),
can indicate the type of energy storage as
Of the energy storage device
At the scheduled time
Is the minimum value of the input power of (1).
Can indicate the type of energy storage as
Of the energy storage device
At the scheduling time
Of the input power of (a). In the formula (31), the reaction mixture,
can indicate the type of energy storage as
Of the energy storage device
At the scheduling time
Of the output power of (c).
Can indicate the type of energy storage as
Energy storage device of
At the scheduling time
Is measured. The equations (30) and (31) may respectively represent the energy storage type as
Energy storage device of
The charging and discharging power limitation of (1). The charge and discharge power limits may include a power limit to increase energy and a power limit to discharge energy. In the formula (32), the reaction mixture is,
can indicate the type of energy storage as
Energy storage device of
The minimum value of the stored energy.
Can indicate the type of energy storage as
Of the energy storage device
The maximum value of the stored energy.
Can indicate the type of energy storage as
Of the energy storage device
At the scheduled time
The stored energy of (2). Equation (32) may represent the capacity limit of the energy storage device described above. In the formula (33), the reaction mixture,
can indicate the type of energy storage as
Energy storage device of
The rate of energy dissipation.
Can indicate the type of energy storage as
Energy storage device of
The charging efficiency of (2).
Can indicate the type of energy storage as
Energy storage device of
The discharge efficiency of (1). The formula (33) can indicate that the energy storage type is
Energy storage device of
The relationship between the stored energy and the charge/discharge power. In the formula (34), the reaction mixture is,
can indicate the type of energy storage as
Energy storage device of
Initial energy storage.
The above-mentioned respective electric vehicle constraints may be expressed according to the following formula:
wherein, in the formula (35),
can represent an electric automobile
Is the probability density function of the daily mileage traveled.
Can show that the electric automobile is in the scheduled time
The daily mileage traveled.
Can represent an electric automobile
Miles traveled.
Can represent an electric automobile
The variance of miles driven on each day that has been driven.
Can represent an electric automobile
Average of miles driven on each day that has been driven. In the formula (36), the reaction mixture is,
can represent an electric automobile
At the scheduling time
The state of charge of (a).
Can represent an electric automobile
State of charge at schedule time 0.
Can representElectric automobile
Minimum value of state of charge of (a).
Can represent an electric automobile
Power consumption of hundreds of kilometers.
Can represent an electric automobile
The rated capacity of (a).
Can represent an electric automobile
Charging efficiency and discharging efficiency. In the formula (37), the reaction mixture is,
it is possible to indicate the battery capacity that each of the electric vehicles included in the above electric vehicles can provide.
The above-described respective integrated demand-side response constraints may be expressed according to the following equation:
wherein, in the formula (38),
a set of load types may be represented.
Can indicate the type of load
At the scheduling time
Load that can be shifted in.
Can indicate the type of load
At the scheduled time
The load that can be transferred out. In the formula (39), the reaction mixture is,
can indicate the type of load
The minimum value of the load that can be shifted in.
Can indicate the type of load
The maximum value of the load that can be transferred. In the formula (40), the reaction mixture is,
can indicate the type of load
The minimum value of the load that can be transferred.
Can indicate the type of load
Maximum value of load that can be transferred. In the formula (41), the compound represented by the formula,
can indicate the type of load
Minimum value of the load that can be interrupted.
Can indicate the type of load
Maximum value of the load that can be interrupted.
Can indicate the type of load
At the scheduling time
The load can be interrupted. In the formula (42), the compound represented by the formula (I),
can represent the type of the load after the response on the comprehensive demand side
At the scheduling time
The load of (2).
Can indicate the type of load
The base load of (2). The base load may be a predetermined load.
Each of the above-mentioned backup constraints may be expressed according to the following equation:
wherein, in the formula (43),
may represent the energy storage device described above.
May represent the above-mentioned electrical energy storage device
Is measured.
May represent the above-mentioned electrical energy storage device
The output power of (1).
Can represent an electric automobile
At the scheduled time
The output power of (1).
A maximum rating for the rotational reserve power of the virtual plant system at safe operation may be represented. The rotational standby power may be a rotational standby power. The maximum rating may be predetermined. In the formula (44), the reaction mixture is,
may represent the above-mentioned electrical energy storage device
Of the input power of (a).
May represent the above-mentioned electrical energy storage device
The input power of (c).
Can represent an electric automobile
At the scheduled time
The input power of (1).
A minimum rated value of the rotating reserve power at which the virtual power plant system is safely operating may be represented. The minimum rating may be predetermined.
The respective energy balance constraints described above may be expressed according to the following equation:
wherein, in the formula (45),
can indicate at the scheduled time
The resulting electrical power.
Can indicate at the scheduled time
Electrical power taken from an energy grid.
May represent the respective electrical energy storage devices comprised by the energy storage device.
Can represent an electrical energy storage device
At the scheduled time
The electrical power of (c). In the formula (46), the reaction mixture is,
can indicate at the scheduled time
Total electrical power of (c). In the formula (47), the compound represented by the formula (47),
can indicate at the scheduled time
The total heat energy of (a).
Can indicate at the scheduled time
Of the heat energy obtained from the energy grid.
It may represent the respective thermal energy storage devices comprised by the energy storage device.
Can represent heat energy storage equipment
At the scheduled time
Of the power of (c). In the formula (48), the reaction mixture is,
can indicate at the scheduled time
Total natural gas energy of.
Can indicate at the scheduled time
Natural gas energy obtained from an energy grid.
May represent the individual natural gas energy storage devices comprised by the energy storage device described above.
Can represent natural gas energy storage equipment
At the scheduled time
Of the power of (c). In the formula (49), the reaction mixture is,
can indicate at the scheduled time
Total hydrogen energy of (a).
It may represent the respective hydrogen storage devices comprised by the energy storage device described above.
Can represent a hydrogen storage facility
At the scheduling time
Of the power of (c).
In practice, the executing entity may generate the energy dispatching target value and the parameter information of each target energy device according to the following formula based on the preset constraint condition set and the generated value information of each energy acquisition device:
wherein, in the formula (51),
the energy scheduling target value may be represented.
Energy acquisition value information that may represent the acquisition of energy from an energy grid.
Can be expressed according to the following formula:
wherein, in the formula (52),
the electric energy acquisition value information (for example, electric energy acquisition cost) of acquiring electric energy from the energy grid may be represented.
Thermal energy capture value information (e.g., thermal energy capture cost) that may represent the capture of thermal energy from an energy grid.
Natural gas acquisition value information (e.g., natural gas acquisition cost) that may represent the acquisition of natural gas from an energy grid.
wherein, in the formula (53),
can indicate the type of load
The transferable load supplement value of (1). The transferable load added value may be added value to the load that can be transferred.
Can indicate the type of load
The interruptible load supplement value of (c). The interruptible load supplement value may be a supplement value of a load that can be interrupted.
Optionally, before step 103, the executing body may execute the following steps:
the method comprises the steps of firstly, determining a preset time period set corresponding to any first historical photovoltaic power group in a first historical photovoltaic power group set as a target time period set. And the first historical photovoltaic power in any first historical photovoltaic power group corresponds to a preset time period in the preset time period set. The correspondence between the first historical photovoltaic power in any of the first historical photovoltaic power groups and the preset time period in the preset time period set may be one-to-one. The number of the first historical photovoltaic power groups included in the first historical photovoltaic power group set is a first numerical value. The first historical photovoltaic power group included in the first historical photovoltaic power group set may be a historical actual photovoltaic power group. The first historical photovoltaic power group may be historical data of photovoltaic power of each preset time period in units of days. The preset time period may be a preset time period in hours in a day. For example, the preset time period may be a historical time period with an interval time of one hour.
A second step of, for each target time period in the set of target time periods, performing the following steps:
and a first substep of fitting each first historical photovoltaic power corresponding to the target time period and included in the first historical photovoltaic power group set to obtain a first historical photovoltaic power distribution function corresponding to the target time period. In practice, the executing body may fit, according to a least square method, each of the first historical photovoltaic powers corresponding to the target time period included in the first historical photovoltaic power group set to obtain a first historical photovoltaic power distribution function corresponding to the target time period.
And a second substep, performing sampling processing on the first historical photovoltaic power distribution function to obtain a second historical photovoltaic power set and a first historical photovoltaic power quantity set corresponding to the target time period. And the second historical photovoltaic power in the second historical photovoltaic power set corresponds to the first historical photovoltaic power quantity in the first historical photovoltaic power quantity set. The correspondence between the second historical photovoltaic power in the second historical photovoltaic power set and the first historical photovoltaic power quantity in the first historical photovoltaic power quantity set may be one-to-one. Each first historical photovoltaic power quantity in the first historical photovoltaic power quantity set corresponds to a second historical photovoltaic power sampling interval. The first historical photovoltaic power quantity is the quantity of the first historical photovoltaic power in each first historical photovoltaic power within the second historical photovoltaic power sampling interval. In practice, first, the execution main body may collect a preset number of sampling points equidistantly on a curve of the first historical photovoltaic power distribution function in order from small to large. Then, the ordinate of each two adjacent sampling points in the preset numerical value sampling points can be combined into a second historical photovoltaic power sampling interval, so as to obtain a second historical photovoltaic power sampling interval set. The second historical photovoltaic power sampling interval may be a closed interval. Then, for each second historical photovoltaic power sampling interval in the second historical photovoltaic power sampling interval set, an average value of first historical photovoltaic powers existing in the second historical photovoltaic power sampling interval in the first historical photovoltaic powers may be determined as a second historical photovoltaic power, so as to generate a second historical photovoltaic power set. The preset value may be a preset value. Secondly, for each second historical photovoltaic power sampling interval in the second historical photovoltaic power sampling interval set, the number of first historical photovoltaic powers existing in the second historical photovoltaic power sampling interval in each first historical photovoltaic power may be determined as a first historical photovoltaic power number, so as to generate a first historical photovoltaic power number set.
And thirdly, determining each generated second historical photovoltaic power set as a second historical photovoltaic power group set. In practice, the executing entity may use each second historical photovoltaic power included in a second historical photovoltaic power set corresponding to the same second historical photovoltaic power sampling interval as a second historical photovoltaic power group to determine a second historical photovoltaic power group set.
And fourthly, for each second historical photovoltaic power group in the second historical photovoltaic power group set, generating a second historical photovoltaic power group probability value corresponding to the second historical photovoltaic power group according to the first historical photovoltaic power quantity set corresponding to the second historical photovoltaic power group and the first numerical value. In practice, first, the executing entity may determine, for each second historical photovoltaic power group in the second historical photovoltaic power group set, a sum of respective first historical photovoltaic power quantities in a first historical photovoltaic power quantity set corresponding to the second historical photovoltaic power group as a first historical photovoltaic power quantity sum. And then, taking the ratio of the first historical photovoltaic power quantity to the first numerical value as a second historical photovoltaic power group probability value corresponding to the second historical photovoltaic power group.
In some optional implementation manners of some embodiments, the executing body may generate the energy scheduling target value and the parameter information of each target energy device by, based on the preset constraint condition set and the generated value information of each energy acquisition device, the following steps:
and step one, determining the energy acquisition value information as an objective function input parameter set.
And secondly, generating a scheduling optimization objective function according to the objective function input parameter set. In practice, the execution subject may input the set of objective function input parameters into an initial objective function to generate a scheduling optimization objective function. Wherein the initial objective function can be expressed according to the following formula:
wherein the content of the first and second substances,
can represent the first
Actual probability values corresponding to the second historical photovoltaic power groups. The actual probability value may be a probability value corresponding to the second historical photovoltaic power group when the photovoltaic system operates at the scheduling time.
May represent the feasible ranges of the individual photovoltaic system output powers described above.
The second historical set of photovoltaic power groups may be represented.
And thirdly, determining a first constraint condition set, a second constraint condition set and a third constraint condition set based on the constraint condition sets. In practice, first, the execution subject may determine, as the first constraint set, the constraint condition that restricts the startup and shutdown of the cogeneration unit in the constraint set. The first set of constraints may include equations (24), (25), and (26). Next, the constraint conditions that constrain the natural gas consumption amount of the cogeneration unit among the set of constraint conditions are determined as a third set of constraint conditions. The third set of constraints may include equation (23). Finally, the constraint conditions in the constraint condition set that are different from the first constraint condition included in the first constraint condition set and the third constraint condition included in the third constraint condition set are determined as a second constraint condition set. The second set of constraints may include equations (11) to (23) and (27) to (50).
And fourthly, determining a fourth constraint condition set according to the generated second historical photovoltaic power group probability values. Wherein the fourth constraint condition set includes a fourth constraint condition based on a 1 norm and a fourth constraint condition based on an infinite norm. In practice, first, the executing entity may adopt a 1-norm, and determine the fourth constraint condition based on the 1-norm according to the generated second historical photovoltaic power group probability values. The above-mentioned respective fourth constraint based on 1 norm may be expressed according to the following formula:
wherein the content of the first and second substances,
can represent the first
A second historical photovoltaic power group probability value for each second historical photovoltaic power group.
May represent a predetermined parameter.
Secondly, determining fourth constraint conditions based on infinite norms according to the generated second historical photovoltaic power group probability values by adopting infinite norms. The above-mentioned respective fourth constraint conditions based on infinite norm may be expressed according to the following formula:
wherein, the first and the second end of the pipe are connected with each other,
may represent a predetermined parameter.
Finally, the generated fourth constraints based on 1 norm and the generated fourth constraints based on infinite norms are combined into a fourth constraint condition set.
And fifthly, performing linearization processing on each fourth constraint condition included in the fourth constraint condition set to generate a linear constraint condition, so as to obtain a linear constraint condition set. The linear constraint set includes respective 1-norm linear constraints and respective infinite-norm linear constraints. In practice, first, the execution subject may convert each 1-norm-based fourth constraint included in the fourth constraint set into each 1-norm linear constraint by using a first auxiliary variable, where each 1-norm linear constraint may be represented by the following equation:
wherein the content of the first and second substances,
a preset first auxiliary variable may be represented.
Secondly, using a second auxiliary variable, converting each fourth constraint condition based on an infinite norm included in the fourth constraint condition set into each infinite norm linear constraint condition, where each infinite norm linear constraint condition may be represented according to the following equation:
wherein, the first and the second end of the pipe are connected with each other,
a predetermined second auxiliary variable may be represented.
And sixthly, generating an energy dispatching target value and parameter information of each target energy device according to the first constraint condition set, the second constraint condition set, the third constraint condition set, the linear constraint condition set and the dispatching optimization objective function. In practice, the executing body may use a column constraint generation algorithm to solve the energy scheduling target value and the parameter information of each target energy device according to the first constraint condition set, the second constraint condition set, the third constraint condition set, the linear constraint condition set, and the scheduling optimization objective function.
The above formula and its related content are used as an invention point of the embodiment of the disclosure, and the technical problem mentioned in the background art is solved, namely, the accuracy of probability distribution obtained by adopting a random optimization method is low, so that the determined scheduling scheme has poor applicability, and further the effect of controlling the energy device to realize energy conservation and emission reduction during the operation of the virtual power plant is poor. Factors that cause poor effects of energy conservation and emission reduction when the energy source device is controlled to realize the virtual power plant operation are as follows: the probability distribution obtained by the random optimization method is low in accuracy, and the scheduling scheme determined by the method is poor in applicability, so that the effect of controlling the energy device to achieve energy conservation and emission reduction during the operation of the virtual power plant is further poor. If the factors are solved, the effect of improving the effect of energy conservation and emission reduction when the energy source control device realizes the operation of the virtual power plant can be achieved. To achieve this effect, in the energy device control method according to some embodiments of the present disclosure, first, the respective energy acquisition value information is determined as an objective function input parameter set. Thereby, an objective function input parameter set may be obtained, which may be used for generating energy scheduling target values. And secondly, generating a scheduling optimization objective function according to the objective function input parameter set. Thus, a scheduling optimization objective function can be obtained, which can be used to generate various target energy device parameter information. Then, based on the above set of constraints, a first set of constraints, a second set of constraints, and a third set of constraints are determined. Thus, uncertainty in the photovoltaic system power generation can be taken into account and can thus be used to generate an optimal solution. And then, determining a fourth constraint condition set according to the generated second historical photovoltaic power group probability values. Wherein the fourth constraint condition set includes a fourth constraint condition based on a 1 norm and a fourth constraint condition based on an infinite norm. Therefore, a fourth constraint condition set comprising a fourth constraint condition based on a 1 norm and a fourth constraint condition based on an infinite norm can be obtained, and robustness and conservatism of the optimal solution of the scheduling optimization objective function can be improved. Next, each fourth constraint condition included in the fourth constraint condition set is linearized to generate a linear constraint condition, and a linear constraint condition set is obtained. Therefore, a linear constraint condition set can be obtained, and the solving difficulty of the scheduling optimization objective function can be reduced. And finally, generating an energy dispatching target value and parameter information of each target energy device according to the first constraint condition set, the second constraint condition set, the third constraint condition set, the linear constraint condition set and the dispatching optimization objective function. Thus, the energy scheduling target value and the parameter information of each target energy device can be obtained. Therefore, the energy device can be controlled to carry out energy scheduling according to the energy scheduling target value and the parameter information of each target energy device, and the effect of energy conservation and emission reduction when the energy device is controlled to realize the operation of the virtual power plant is improved. The obtained energy scheduling target value and parameter information of each target energy device are generated under the condition that a linear constraint condition set based on 1 norm and infinite norm is comprehensively considered, so that the accuracy of the probability distribution of the generating power of the photovoltaic system can be improved, and the effect of controlling the energy device to realize energy conservation and emission reduction during the operation of the virtual power plant is further improved.
And 104, controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device.
In some embodiments, the executing agent may control each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device in various manners. In practice, first, the executing entity may control each photovoltaic system in various ways to make the parameter information of the photovoltaic system during operation at each scheduling time be the same as the parameter information of each target energy device of the corresponding photovoltaic system. And controlling each cogeneration unit to enable the parameter information of the cogeneration unit in operation at each scheduling time to be the same as the parameter information of each target energy device of the corresponding cogeneration unit. And controlling each electric power conversion device to enable the parameter information of the electric power conversion device in operation at each scheduling time to be the same as the parameter information of each target energy device of the corresponding electric power conversion device. And controlling each electric energy storage device, each thermal energy storage device, each natural gas energy storage device and each hydrogen storage device, so that the parameter information of the electric energy storage device in operation at each scheduling time is the same as the parameter information of each target energy device of the corresponding electric energy storage device, the parameter information of the thermal energy storage device in operation at each scheduling time is the same as the parameter information of each target energy device of the corresponding thermal energy storage device, the parameter information of the natural gas energy storage device in operation at each scheduling time is the same as the parameter information of each target energy device of the corresponding natural gas energy storage device, and the parameter information of the hydrogen storage device in operation at each scheduling time is the same as the parameter information of each target energy device of the corresponding hydrogen storage device. And controlling each electric automobile to enable the parameter information of the electric automobile in the running process at each scheduling time to be the same as the parameter information of each target energy device of the corresponding electric automobile.
In some optional implementations of some embodiments, the executing entity may control each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device by:
the method comprises the steps of responding to the condition that the current time meets the preset energy scheduling time, generating energy device control information corresponding to each energy device included in each energy device, and obtaining an energy device control information set. The preset energy scheduling time condition may be that the current time is the same as a preset time for executing the energy scheduling task. The energy device control information may characterize the energy device as beginning to perform an energy scheduling task. In practice, the execution body may combine the energy device identifier of the energy device with information indicating that the execution of the energy scheduling task is started, and generate energy device control information corresponding to the energy device. The above combination may be character concatenation.
And secondly, controlling each energy device to execute an energy scheduling task according to the parameter information of each target energy device according to the energy device control information set. In practice, for each energy device control information included in the above-mentioned energy device control information set, the following sub-steps are performed:
a first substep of determining target energy device parameter information corresponding to the energy device control information among the target energy device parameter information as candidate target energy device parameter information, to obtain a candidate target energy device parameter information set. The target energy device parameter information corresponding to the energy device control information may be target energy device parameter information of the energy device corresponding to the energy device control information.
And a second substep of controlling the energy devices corresponding to the energy device control information to perform an energy scheduling task according to the candidate target energy device parameter information set, according to the energy device control information.
Optionally, the executing body may execute the following steps:
and step one, receiving triggering information of each energy scheduling task sent by each energy device. And the energy devices included in each energy device correspond to the energy scheduling task trigger information included in each energy scheduling task trigger information. The energy devices included in the energy devices may correspond to the energy scheduling task trigger information included in the energy scheduling task trigger information one to one. Each energy scheduling task trigger information included in the energy scheduling task trigger information may represent that the energy device corresponding to the energy scheduling task trigger information starts to execute the energy scheduling task.
And a second step of generating energy dispatching starting prompt information in response to the fact that the number of the received energy dispatching task trigger information is the same as that of the energy devices. The energy scheduling start prompt information can indicate that the energy device is prompted to start executing the energy scheduling task. The energy scheduling start prompt message may be a combination of an energy device identifier and a preset character string. The combination mode can be character splicing. For example, the energy scheduling start prompt message may be "the photovoltaic system energy scheduling task starts to execute".
And thirdly, controlling the associated display equipment to display the energy scheduling starting prompt message. The display device may be a display screen communicatively connected to the execution main body.
And fourthly, receiving the completion information of each energy scheduling task sent by each energy device. And the energy devices included in each energy device correspond to the energy scheduling task completion information included in the energy scheduling task completion information. The energy devices included in the energy devices may correspond to the energy scheduling task completion information included in the energy scheduling task completion information one to one. Each energy scheduling task completion information included in the energy scheduling task completion information may represent that the energy device corresponding to the energy scheduling task completion information completes an energy scheduling task.
And fifthly, in response to the fact that the number of the received energy scheduling task completion messages is the same as that of the energy devices, generating energy scheduling completion prompt messages. The energy scheduling completion prompt information can be used for prompting all energy devices to complete energy scheduling tasks. The energy scheduling completion prompt message may be a message of a character combination. The combination mode can be character splicing. For example, the energy scheduling completion prompt message may be "energy scheduling task completion".
And sixthly, controlling the display equipment to display the energy scheduling completion prompt message.
Optionally, the executing body may execute the following steps:
and step one, receiving triggering information of each energy scheduling task sent by each energy device. And the energy devices included in the energy devices correspond to the energy scheduling task trigger information included in the energy scheduling task trigger information. The energy devices included in the energy devices may correspond to the energy scheduling task trigger information included in the energy scheduling task trigger information one to one. Each energy scheduling task trigger information included in the energy scheduling task trigger information may characterize the energy device corresponding to the energy scheduling task trigger information to start executing the energy scheduling task.
And a second step of generating an energy dispatching starting sound prompt message in response to the fact that the number of the received energy dispatching task trigger messages is the same as that of the energy devices. The energy scheduling starting voice prompt message can indicate that the energy device is prompted to start executing the energy scheduling task. The energy scheduling start audible prompt message may be a combination of an energy device identifier and corpus information. The above combination may be character concatenation. The corpus information may be "energy scheduling task start execution". For example, the energy scheduling start audible prompt message may be "photovoltaic system energy scheduling task start execution".
And thirdly, controlling the associated sound equipment to play the energy scheduling starting sound prompt message. The sound equipment can be a sound player.
And fourthly, receiving the completion information of each energy scheduling task sent by each energy device. And the energy devices included in the energy devices correspond to the energy scheduling task completion information included in the energy scheduling task completion information. The energy devices included in the energy devices may correspond to the energy scheduling task completion information included in the energy scheduling task completion information one to one. Each energy scheduling task completion information included in the energy scheduling task completion information may represent that the energy device corresponding to the energy scheduling task completion information completes an energy scheduling task.
And fifthly, in response to the fact that the number of the received energy scheduling task completion messages is the same as that of the energy devices, generating energy scheduling completion sound prompt messages. The energy scheduling completion sound prompt information can represent and prompt all energy devices to complete energy scheduling tasks. The energy scheduling completion sound prompt information may be corpus information. The corpus information may be "all energy devices energy scheduling tasks complete".
And sixthly, controlling the sound equipment to play the energy scheduling completion sound prompt message.
The above embodiments of the present disclosure have the following advantages: by the energy device control method of some embodiments of the disclosure, comprehensiveness of energy scheduling parameters can be improved, so that applicability of a scheduling scheme is improved, and effects of energy conservation and emission reduction during operation of a virtual power plant are further improved by controlling the energy device. Specifically, the reason why the effect of energy conservation and emission reduction is poor when the energy source control device realizes the virtual power plant operation is that: the energy dispatching of the virtual power plant is realized by controlling a single energy device through a random optimization method, the comprehensiveness of parameter information influencing the energy dispatching is poor, and the applicability of the dispatching scheme determined by the comprehensiveness is poor, so that the effect of controlling the energy device to realize energy conservation and emission reduction during the operation of the virtual power plant is poor. Based on this, the energy device control method of some embodiments of the present disclosure first acquires an energy device information set corresponding to each energy device of the virtual power plant. Wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information, and an energy device number. Therefore, parameter information which influences energy scheduling comprehensively can be obtained, and the method can be used for generating each energy acquisition value information. Then, for each energy device information included in the energy device information set, energy acquisition value information corresponding to the energy device information is generated based on the energy device name, the energy device parameter information, and the energy device number included in the energy device information. Thus, the obtained energy acquisition value information can be used as value constraint for generating the energy scheduling target value and the parameter information of each target energy device. Then, based on the preset constraint condition set and the generated value information of each energy acquisition, an energy scheduling target value and parameter information of each target energy device are generated. Wherein the set of constraints includes constraints characterizing a constraint on at least one energy device parameter information included in the set of energy device information. Therefore, the optimized energy scheduling target value and the parameter information of each target energy device can be obtained, and a scheduling scheme with good adaptability is determined according to the obtained optimized energy scheduling target value and the parameter information of each target energy device. And finally, controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device. Therefore, each energy device of the virtual power plant can be controlled to execute the energy scheduling task according to the scheduling scheme. And the parameter information influencing energy scheduling is considered relatively comprehensively, and the scheduling scheme is determined according to the parameter information, so that the applicability of determining the scheduling scheme according to the parameter information can be improved. And each energy device of the virtual power plant can be controlled to execute an energy scheduling task according to the scheduling scheme, so that the effect of controlling the energy devices to realize energy conservation and emission reduction during the operation of the virtual power plant is improved. Therefore, the comprehensiveness of the energy dispatching parameters can be improved, the applicability of the dispatching scheme is improved, and the effect of energy conservation and emission reduction during the operation of the virtual power plant is further improved by controlling the energy source device.
With further reference to fig. 2, as an implementation of the methods illustrated in the above figures, the present disclosure provides some embodiments of an energy device control apparatus, which correspond to those method embodiments illustrated in fig. 1, and which may be particularly applicable in various electronic devices.
As shown in fig. 2, the energy device control device 200 of some embodiments includes: an acquisition unit 201, a first generation unit 202, a second generation unit 203, and a control unit 204. Wherein the acquiring unit 201 is configured to acquire an energy device information set corresponding to each energy device of the virtual power plant, wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information, and an energy device number; the first generation unit 202 is configured to generate, for each energy device information included in the energy device information set, energy acquisition value information corresponding to the energy device information, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information; the second generating unit 203 is configured to generate an energy scheduling target value and each target energy device parameter information based on a preset constraint condition set including a constraint condition characterizing constraint on at least one energy device parameter information included in the energy device information set, and the generated each energy acquisition value information; and the control unit 204 is configured to control each energy device of the virtual power plant to perform an energy scheduling task according to the target energy device parameter information.
It will be understood that the units described in the apparatus 200 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above for the method are also applicable to the apparatus 200 and the units included therein, and are not described herein again.
Referring now to FIG. 3, a block diagram of an electronic device (e.g., a computing device or terminal device) 300 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device in some embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle-mounted terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 300 to communicate wirelessly or by wire with other devices to exchange data. While fig. 3 illustrates an electronic device 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 3 may represent one device or may represent multiple devices, as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. The computer program, when executed by the processing apparatus 301, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may be separate and not incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring an energy device information set corresponding to each energy device of a virtual power plant, wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information and an energy device number; generating energy acquisition value information corresponding to the energy device information for each piece of energy device information included in the energy device information set, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information; generating an energy scheduling target value and parameter information of each target energy device based on a preset constraint condition set and the generated value information of each energy acquisition, wherein the constraint condition set comprises constraint conditions representing constraint on at least one piece of energy device parameter information included in the energy device information set; and controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a first generation unit, a second generation unit, and a control unit. Here, the names of the units do not constitute a limitation to the units themselves in some cases, and for example, the acquiring unit may also be described as a "unit that acquires energy device information sets of the respective energy devices of the corresponding virtual power plants".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (7)
1. An energy device control method comprising:
acquiring an energy device information set corresponding to each energy device of a virtual power plant, wherein each energy device information included in the energy device information set comprises an energy device name, energy device parameter information and an energy device number;
generating energy acquisition value information corresponding to the energy device information for each piece of energy device information included in the energy device information set, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information;
determining a preset time period set corresponding to any first historical photovoltaic power group in a first historical photovoltaic power group set as a target time period set, wherein the first historical photovoltaic power in the any first historical photovoltaic power group corresponds to the preset time period in the preset time period set, and the number of the first historical photovoltaic power groups included in the first historical photovoltaic power group set is a first numerical value;
for each target time period in the set of target time periods, performing the steps of:
fitting each first historical photovoltaic power corresponding to the target time period and included in the first historical photovoltaic power group set to obtain a first historical photovoltaic power distribution function corresponding to the target time period;
sampling the first historical photovoltaic power distribution function to obtain a second historical photovoltaic power set and a first historical photovoltaic power quantity set corresponding to the target time period, wherein the second historical photovoltaic power in the second historical photovoltaic power set corresponds to the first historical photovoltaic power quantity in the first historical photovoltaic power quantity set, each first historical photovoltaic power quantity in the first historical photovoltaic power quantity set corresponds to a second historical photovoltaic power sampling interval, and the first historical photovoltaic power quantity is the quantity of the first historical photovoltaic power in each first historical photovoltaic power sampling interval;
determining each generated second historical photovoltaic power set as a second historical photovoltaic power group set;
for each second historical photovoltaic power group in the second historical photovoltaic power group set, generating a second historical photovoltaic power group probability value corresponding to the second historical photovoltaic power group according to a first historical photovoltaic power quantity set corresponding to the second historical photovoltaic power group and the first numerical value;
generating an energy scheduling target value and parameter information of each target energy device based on a preset constraint condition set and the generated value information of each energy acquisition, wherein the constraint condition set comprises constraint conditions representing constraint on at least one piece of energy device parameter information included in the energy device information set;
and controlling each energy device of the virtual power plant to execute an energy scheduling task according to the parameter information of each target energy device.
2. The method of claim 1, wherein the controlling each energy device of the virtual power plant to perform an energy scheduling task according to the each target energy device parameter information comprises:
in response to determining that the current time meets a preset energy scheduling time condition, generating energy device control information corresponding to each energy device included in each energy device to obtain an energy device control information set;
and controlling each energy device to execute an energy scheduling task according to the parameter information of each target energy device according to the energy device control information set.
3. The method of claim 1, wherein the method further comprises:
receiving triggering information of each energy scheduling task sent by each energy device;
in response to determining that the number of received energy scheduling task trigger messages is the same as the number of energy devices, generating energy scheduling start prompt messages;
controlling the associated display equipment to display the energy scheduling starting prompt message;
receiving each energy scheduling task completion information sent by each energy device;
in response to determining that the number of received energy scheduling task completion messages is the same as the number of energy devices, generating energy scheduling completion prompt messages;
and controlling the display equipment to display the energy scheduling completion prompt information.
4. The method of claim 1, wherein the method further comprises:
receiving triggering information of each energy scheduling task sent by each energy device;
in response to determining that the number of received individual energy scheduling task trigger messages is the same as the number of the individual energy devices, generating an energy scheduling onset audible prompt message;
controlling the associated sound equipment to play the energy scheduling starting sound prompt message;
receiving each energy scheduling task completion information sent by each energy device;
in response to determining that the number of received energy scheduling task completion messages is the same as the number of energy devices, generating energy scheduling completion audible prompt messages;
and controlling the sound equipment to play the energy scheduling completion sound prompt information.
5. An energy device control device comprising:
an acquisition unit configured to acquire an energy device information set corresponding to each energy device of a virtual power plant, wherein each energy device information included in the energy device information set includes an energy device name, energy device parameter information, and an energy device number;
a first generation unit configured to generate, for each energy device information included in the energy device information set, energy acquisition value information corresponding to the energy device information, based on an energy device name, energy device parameter information, and an energy device number included in the energy device information;
the device comprises a first determining unit and a second determining unit, wherein the first determining unit is configured to determine a preset time period set corresponding to any first historical photovoltaic power group in a first historical photovoltaic power group set as a target time period set, the first historical photovoltaic power in the any first historical photovoltaic power group corresponds to a preset time period in the preset time period set, and the number of the first historical photovoltaic power groups included in the first historical photovoltaic power group set is a first numerical value;
an execution unit configured to, for each target time period in the set of target time periods, perform the steps of:
fitting each first historical photovoltaic power corresponding to the target time period and included in the first historical photovoltaic power group set to obtain a first historical photovoltaic power distribution function corresponding to the target time period;
sampling the first historical photovoltaic power distribution function to obtain a second historical photovoltaic power set and a first historical photovoltaic power quantity set corresponding to the target time period, wherein a second historical photovoltaic power in the second historical photovoltaic power set corresponds to a first historical photovoltaic power quantity in the first historical photovoltaic power quantity set, each first historical photovoltaic power quantity in the first historical photovoltaic power quantity set corresponds to a second historical photovoltaic power sampling interval, and the first historical photovoltaic power quantity is the quantity of a first historical photovoltaic power in each first historical photovoltaic power sampling interval;
a second determination unit configured to determine the generated respective second historical photovoltaic power sets as second historical photovoltaic power group sets;
a probability value generation unit configured to generate, for each of the second historical photovoltaic power group sets, a second historical photovoltaic power group probability value corresponding to the second historical photovoltaic power group according to a first historical photovoltaic power quantity set corresponding to the second historical photovoltaic power group and the first numerical value;
a second generation unit configured to generate an energy scheduling target value and each target energy device parameter information based on a preset constraint condition set including a constraint condition characterizing constraint on at least one energy device parameter information included in the energy device information set, and the generated each energy acquisition value information;
a control unit configured to control each energy device of the virtual power plant to perform an energy scheduling task according to the each target energy device parameter information.
6. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method recited in any of claims 1-4.
7. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-4.
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| CN115036993A (en) | 2022-09-09 |
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